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The New Psychology: Rules Vs. Network Activations

By: , Posted on: March 7, 2016

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This is the second in my four-part blog about The New Psychology. It elaborates the observation that I made in my previous blog that Old Psychology continues to suffer from the mind-body (brain) problem. A recent appraisal of psychology and neuroscience by Schwartz, Lilienfeld, Meca, and Savigné (2016) clearly illustrates that this is so. Their appraisal is predicated upon a “levels of analysis” concept also known as “explanatory levels” and “hierarchy of explanation”. The levels are psychology and biology. The authors repeatedly called for “bridge laws” to connect these two separate levels. Presenting psychology and biology as levels of analysis and calling for bridging laws to connect these two levels is a restatement of the mind-body (brain) problem and not a solution of it. This problem has been around since René Descartes (1596-1650) unfortunately proposed that mind differs from brain. Old Psychology has faced this problem since 1879 when Wilhelm Wundt opened the Institute for Experimental Psychology at the University of Leipzig in Germany. No workable solution has arrived since nor is it likely that one will ever arrive so long as Old Psychology is practiced. A large part of the problem is that Old Psychology relies on rules and symbols to explain psychology and behavior.

Old Psychology is centered on the mind, which thinks, feels, and behaves by using rules to manipulate symbols. Old Psychology claims that these rules are like psychological software that runs on brain hardware. This claim makes psychology independent of neuroscience in the same way that software is independent of hardware. This analogy does not hold as well as proponents maintain. For example, parallel processing software cannot operate on hardware that supports only serial processing. But for present purposes we will accept this largely true analogy on the basis that people who write computer code, software, do not also have to be hardware engineers. This distinction between software and hardware is a declaration of independence of psychology from neuroscience. This declaration of independence is supposed to protect psychology from greedy reductionism that threatens to replace psychology with neuroscience. Unfortunately, this declaration of independence is problematic because it isolates Old Psychology from neuroscience and other natural sciences. Emphasizing the irrelevance of neuroscience to psychology inhibits to prohibits integrating psychology and neuroscience. It forces Old Psychology to continue to search for the psychological mechanisms that my previous blog explained do not exist because they cannot exist because there is no psychological substrate for them to operate on. This declaration of independence discourages to prohibits a search for how psychology emerges from biology. The history of successful science is one of consilience; a term that Wilson (1998) coined to describe the unity of science and how natural sciences work together and build upon one another. This going-it-alone approach almost certainly means that Old Psychology will be replaced by New Psychology. The reasons against rule-based explanations presented below are additional reasons to transition from Old Psychology to New Psychology now.

Reasons Against Rule-based Explanations

The first, and I think fatal, reason why the search for rule-based explanations is fatally flawed is, as I mentioned above and in my previous blog, that there is no psychological substrate for psychological mechanisms such as rules to operate on and therefore there is no way that rules can physically govern what the brain does. Unlike software that is physically present as binary states in a machine, psychological rules are mere metaphors. They are abstractions created by investigators based on perceived similarities between what brains do and what computers do. Neither brain scans nor brain surgery has revealed anything like rules inside the brain in the same way as software commands can be found inside computers. Rules are inferences by investigators and not physical brain objects. Rules have no physical reality. Rules therefore cannot possibly provide a natural science explanation of how the brain and therefore psychology works.

A related second reason why rule-based explanations are fatally flawed is that they have an explanatory gap that they cannot close. Software actually governs what computers do. Computer behavior can be explained in software terms. One looks to computer code to explain why a computer did or did not do something of interest. Old Psychology believes that parallel explanations can be found for how people think and behave. Their view is that one needs to examine the rules that the mind follows to explain psychology and behavior. The mind-body (brain) problem arises when one asks how mental rules get the body to behave accordingly. As per a famous cartoon that comments on a critical step in causal reasoning, “something magical happens about here”. This is where unstated bridging laws are needed. Curiously, identifying these bridging laws appears to lay outside of Old Psychology which means that providing an adequate explanation is someone else’s problem. Identifying bridge laws is not a neuroscience problem because neuroscience recognizes only brain not mind on the basis that mind is just a word for what brain does. Mind has no physical existence on its own. Hence, there is nothing to bridge brain to.

A third reason why rule-based explanations are fatally flawed is that they assume consciousness. We reason from assumptions not to them. Hence, a rule-based approach cannot ever explain consciousness which is central to understanding everything psychological.

A fourth reason why rule-based explanations are fatally flawed is that they assume that people learn and form memories. The rule-based approach is silent regarding the mechanics of learning and memory yet virtually everything psychological is the product of learning and memory.

A fifth reason why rule-based explanations are fatally flawed is that they assume that people are completely rational and always fully informed regarding opportunities, risks, and rewards which they clearly are not. Economists share this peculiar view. Kahneman refers to this imagined species as homo-economicus. Instead of developing economic models that pertain to real people, economists and Old Psychology make unrealistic assumptions about people that support their psychological and mathematical models.

A sixth reason why rule-based explanations are fatally flawed is that they assume that people act as if they are computers despite the obvious fact that computers do not have emotions. People clearly have emotions and often act for emotional reasons.

A seventh reason why rule-based explanations are fatally flawed is that there are no emotional rules to govern how people feel. Restricting psychological explanations to following rules excludes explaining emotions and emotion-based behavior.

An eighth reason why rule-based explanations are fatally flawed is that they assume that people will not harm themselves because that is irrational. Yet people smoke, drink too much soda and alcohol, each too much red meat, drive too fast among other self-damaging behaviors.

A ninth reason why rule-based explanations are fatally flawed is that there are no rules that explain how people see, hear, and taste and how they integrate this information into how they think. Rule-based psychology is seriously disconnected from the body.

A tenth reason why rule-based explanations are fatally flawed is that rule-based explanations have been developed on young healthy people, mostly college students. How does aging effect these rules? Are the rules that children follow different from the rules that adolescents follow? Are the rules that adolescents follow different from the rules that adults follow? If so, what are the rules that govern the development of rules over time? How do such meta-rules govern the other rules?

An eleventh reason why rule-based explanations are fatally flawed is that alcohol, drugs, and psychotropic medications alter how people think, feel, and behave. How do these substances alter the rules that people presumably follow? Once the rules are altered by virtue of these substances, how do the rules return to their original state once the substance wears off? Or are the rules changed in some enduring way?

A twelfth reason why rule-based explanations are fatally flawed is that brain damage due to trauma or dementia alters how people think, feel, and behave. How does brain damage alter the rules that people follow? The computer analogy is troubling here. How can physical damage to the central processor change the software? One possibility is that the damage physically removes some of the software. But that requires physical damage of a certain type. What about damage to the hardware that does not store software?

A thirteenth reason why rule-based explanations are fatally flawed is that they are based on serial processing which is several orders of magnitude too slow to explain how insects behave let alone how mammals think and behave. Massive evidence indicates that many life forms process information in parallel; not serially like most computers do. So why constrain psychological explanations to serial processes when we already know that most life forms do not act this way?

These 13 reasons why rule-based explanations are fatally flawed are sufficient to abandon this form of explanation and thereby completely avoid all of these unsolvable self-inflicted problems. Bad theories are rarely, if ever, abandoned because of their problems and deficiencies. It takes a better theory to replace a bad theory. The New Psychology is a better theory because it entirely avoids all of the problems associated with rule-based explanations identified above.

New Psychology

The New Psychology began in 1986 when Rumelhart and McClelland (1986) and McClelland and Rumelhart (1986) provided a way to do psychology with brain-like models thereby avoiding the mind-body (brain) problem and any need to find bridging laws. My book (Tryon, 2014) Cognitive Neuroscience and Psychotherapy: Network Principles for a Unified Theory describes New Psychology in some detail although I refer to it as connectionist neural network models or connectionist psychology. A PsychINFO search on 1/24/16 using the search term “connectionist” returned 2,660 citations. This is clearly too much to summarize in a blog. So I will restrict my comments to a few central points. My fourth blog in this series presents a dozen properties of neural networks as psychological principles.

Connectionist models come in two major forms: Localist, and parallel-distributed-processing (PDP). The PDP models are more biologically relevant than the Localist models are. PDP models consist of three or more layers of processing nodes, simulated neurons, connected by two or more layers of simulated synapses whose connection weights range from -1 indicating maximum inhibition to +1 indicating maximum excitation. Processing nodes in the second and other layers receive multiple inputs called activations. In some models the receiving node fires if and only if the received activations exceed a threshold value. In other models the receiving node fires in direct proportion to the received activations. In this way activations that began at a sensory level propagate across one or more processing levels where psychological phenomena emerge to nodes that govern behavior. The transformations that occur at every level of simulated synapses are integral to the emergence of psychological constructs.

It is the integration of basic neuroscience concepts that makes such brain-like New Psychology models much more attractive than Old Psychology models. The New Psychology models make it easier to understand how and why psychological properties such as learning and memory emerge from functioning neural networks. Every psychological phenomena depends upon learning and memory. Everything that is psychological was learned and memory is required for learning to endure. This full integration with neuroscience means that our understanding of learning and memory can improve with new neuroscience advances as well as with new psychological findings. The ability to work constructively with neuroscience rather than compete with it is a very big reason why New Psychology will continue to replace Old Psychology.

Another reason why the New Psychology is more attractive than Old Psychology is because there is mathematical proof that networks constructed from three or more layers of processing nodes can, in principle, solve problems of any degree of complexity (See Tryon, 2014, p. 363). No such mathematical proof has been provided for rule-based Old Psychology models.

Read more from Warren Tryon on SciTech Connect

Warren’s book, Cognitive Neuroscience and Psychotherapy: Network Principles for a Unified Theory is available for purchase on the Elsevier Store.

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Use discount code “STC215” at checkout and save up to 30% on your very own copy.

About the Author

Warren ComputerWarren W. Tryon received his undergraduate degree from Ohio Northern University in 1966. He was enrolled in the APA approved Doctoral Program in Clinical Psychology at Kent State University from 1966 – 1970. Upon graduation from Kent State, Dr. Tryon joined the Psychology Department faculty at Fordham University in 1970 as an Assistant Professor. He was promoted to Associate Professor in 1977 and to Full Professor in 1983. Licensed as a psychologist in New York State in 1973, he joined the National Register of Health Service Providers in Psychology in 1976, became a Diplomate in Clinical Psychology from the American Board of Professional Psychology (ABPP) in 1984, was promoted to Fellow of Division 12 (Clinical) of the American Psychological Association in 1994 and a fellow of the American Association of Applied and Preventive Psychology in 1996. Also in 1996 he became a Founder of the Assembly of Behavior Analysis and Therapy.

In 2003 he joined The Academy of Clinical Psychology. He was Director of Clinical Psychology Training from 1997 to 2003, and presently is in the third and final year of phased retirement. He will become Emeritus Professor of Psychology in May 2015 after 45 years of service to Fordham University. Dr. Tryon has published 179 titles, including 3 books, 22 chapters, and 140 articles in peer reviewed journals covering statistics, neuropsychology, and clinical psychology. He has reviewed manuscripts for 45 journals and book publishers and has authored 145 papers/posters that were presented at major scientific meetings. Dr. Tryon has mentored 87 doctoral dissertations to completion. This is a record number of completed dissertations at the Fordham University Graduate School of Arts and Sciences and likely elsewhere.

His academic lineage is as follows. His mentor was V. Edwin Bixenstein who studied with O. Hobart Mowrer at the University of Illinois who studied with Knight Dunlap at Johns Hopkins University who studied with Hugo Munsterberg at Harvard University who studied with Wilhelm Wundt at the University of Leipzig.

Cognitive Neuroscience and Psychotherapy: Network Principles for a Unified Theory is Dr. Tryon’s capstone publication. It is the product of more than a quarter of a century of scholarship. Additional material added after this book was printed is available at This includes chapter supplements, a color version of Figure 5.6, and a thirteenth “Final Evaluation” chapter. He is on LinkedIn and Facebook. His email address is

McClelland, J. L., Rumelhart, D. E., & the PDP Research Group (1986). Parallel distributed processing: Explorations in the microstructure of cognition. Psychological and biological models. (Vol. 2) Cambridge, MA: MIT Press.
Rumelhart, D. E., McClelland, J. L., & the PDP Research Group (1986). Parallel distributed processing: Explorations in the microstructure of cognition, Vol. 1: Foundations. Cambridge, MA: MIT Press.
Schwartz, S. J., Lilienfeld, S. O., Meca, A., & Savigné, K. C. (2016). The role of neuroscience within psychology: A call for inclusiveness over exclusiveness. American Psychologist, 71, 52-70. doi 10.1037/a0039678
Tryon, W. W. (2014). Cognitive neuroscience and psychotherapy: Network Principles for a Unified Theory. New York: Academic Press.
Wilson, E. O. (1998). Consilience: The unity of knowledge. New York: Knopf.

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